Abstract
Mesial temporal lobe epilepsy is the most common form of adult epilepsy in surgical series. Currently, the only characteristic used to predict poor response to clinical treatment in this syndrome is the presence of hippocampal sclerosis. Single nucleotide polymorphisms (SNPs) located in genes encoding drug transporter and metabolism proteins could influence response to therapy. Therefore, we aimed to evaluate whether combining information from clinical variables as well as SNPs in candidate genes could improve the accuracy of predicting response to drug therapy in patients with mesial temporal lobe epilepsy. For this, we divided 237 patients into two groups: 75 responsive and 162 refractory to antiepileptic drug therapy. We genotyped 119 SNPs in ABCB1, ABCC2, CYP1A1, CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, and CYP3A5 genes. We used 98 additional SNPs to evaluate population stratification. We assessed a first scenario using only clinical variables and a second one including SNP information. The random forests algorithm combined with leave-one-out cross-validation was used to identify the best predictive model in each scenario and compared their accuracies using the area under the curve statistic. Additionally, we built a variable importance plot to present the set of most relevant predictors on the best model. The selected best model included the presence of hippocampal sclerosis and 56 SNPs. Furthermore, including SNPs in the model improved accuracy from 0.4568 to 0.8177. Our findings suggest that adding genetic information provided by SNPs, located on drug transport and metabolism genes, can improve the accuracy for predicting which patients with mesial temporal lobe epilepsy are likely to be refractory to drug treatment, making it possible to identify patients who may benefit from epilepsy surgery sooner.
Highlights
Mesial temporal lobe epilepsy (MTLE) is the most common form of epilepsy in adults, and it is frequently associated with hippocampal sclerosis (HS), which can be detected by magnetic resonance imaging (MRI) [1, 2]
We used the age of epilepsy onset as a categorical variable, classifying individuals in 10 groups based on five year windows
We show in this study that Single nucleotide polymorphisms (SNPs) information from genes influencing drug metabolism and drug transporters, together with clinical data, can significantly improve the prediction of response to antiepileptic drugs (AEDs) in patients with MTLE, with an estimated accuracy of 0.8177
Summary
Mesial temporal lobe epilepsy (MTLE) is the most common form of epilepsy in adults, and it is frequently associated with hippocampal sclerosis (HS), which can be detected by magnetic resonance imaging (MRI) [1, 2]. Other factors have been implicated in AED drug response (yet not proven), such as gender, age of seizure onset, aetiology of epilepsy, as well as genetic factors including family history of epilepsy and gene mutations affecting proteins involved in AED absorption, metabolism, and transport [3]. ABC genes encode multidrug resistance proteins, and previous studies have suggested that multidrug resistance proteins could decrease drug penetration into the brain of patients with refractory MTLE [4, 6], leading to pharmacoresistance. Because PHT and CBZ are subjected to hepatic metabolism, cytochrome P450 (CYP450) isoenzymes could have an important role, affecting drug exposure in brain tissue, these include CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP1B1 and CYP2E1 proteins [9,10,11,12,13]
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